Month: August 2018

Previously, we have done comparisons on mobile account opening and the design of these offerings as it relates to incumbents vs. FinTechs, so we thought it only fair to do a more detailed comparison based on product offerings and where the industry is headed. While you can call our design evaluation subjective, our side by side product and feature comparison demonstrates how the large incumbents serve a stronger set of offerings to a broader base of investors, but at the expense of simplicity. While the FinTechs have limited offering but a more honed feature set.

Set-It-And-Forget-It

Pretty much everyone is working on some form of a robo, and many have already started their own. In fact, due to competition for passive investors from low fee, automated investing startups like Wealthfront and Betterment, incumbents (Schwab, Fidelity, E*TRADE, TD Ameritrade) were quick to roll out at least one automated investing account and many now offer more than one option.

The start-ups are forcing banks and brokers to adopt technology faster than ever before, while the established players are pushing the robos to incorporate more traditional services in their products. In fact, many of the digital-only startups are layering in human advice to complement their automated offerings. This should give pause to any incumbent, or at the very least, make them rethink their features and user experience.

Robinhood, which earlier this year added crypto trading, only offers this feature in select states. Square added crypto trading to their Cash app in late January, with Square Cash averaging 2M downloads per month, 3x the growth rate of Venmo. Coinbase surpassed Charles Schwab in the number of open accounts in late 2017 (11.7M vs. 10.6M), but the value of those accounts is still a fraction of the value of Schwab ($50B vs. $3.26T)

While all of the challengers in the investing space have well-defined customer journeys and easy to use interfaces, there’s still a large difference in the breadth of the offering. Customers with specialized needs (securities lending, bonds, futures, trust capabilities, advanced options tools) will probably be better served by more established players. While customers seeking to simply capture market returns with excess cash will probably enjoy the better digital experience and onboarding provided by the newer players in retail brokerage.

What interests us is how both facets are pushing the others to be better. FinTech is pushing the incumbents to simplify, while the incumbents are pushing fintech to be more than just a pretty interface. But the question is, will anyone become the Amazon of investing? Will anyone ever have everything for everyone? And what will that look like? Time will certainly tell.

More and more APIs are being adopted across all industries—travel (Google Maps), food/entertainment (OpenTable, Spotify), communication (What’sApp, Messenger, WeChat). Companies like Button are partnering with brands to help distribute their offerings to a large developer community and that are eager to strengthen their mobile experience via the use of APIs. APIs, to these organizations, equal opportunity, and access.

However, when looking at the Finance industry, banks and brokerages are lagging behind in API adoption. Screen-scraping—which we’ve written about numerous times—doesn’t allow for reliable data connections to banks and is a huge security risk. However, screenscrapers are widely used and via the halo effect, end users are tricked into submitting their information that results in loss of control over their own data. All of that can be alleviated with the adoption of APIs which use information in a more effective and efficient way. APIs still allow data sharing but in a way that creates a safe, seamless experience for both users and creators.

Like this:

In our previous post we touched on the potential of an ETF bubble. The exponential growth of ETFs, especially from younger investors who want to set-it-and-forget-it, means there’s an opportunity for providers to increasingly use Artificial Intelligence in smart alpha and active products. But what can AI do for your business and investment strategy?

Like Humans, Only Better, Faster, Smarter

AI tools can intake data, learn from it, and act on it to meet specific objectives. But they can do it more quickly and efficiently. In fact, machines running AI algorithms can process large amounts of data in the blink of an eye. Market data is dynamic. Machines can react instantly to fluctuations to best identify ideal investment strategies. They can also read through thousands of pages of market reports in seconds, while simultaneously connecting new market signals with recent ones detected in other markets. It would take a fund manager hours to do the same thing a machine can do in split seconds.

AI Has No Ego or Emotion

Investors tend to make poor decisions because it’s their money they could lose. Money is emotional. But machines don’t get stressed, tired, or angry. There’s no winning or losing. They operate in a purely logical manner and make decisions based only on evidence and indicators. When you remove emotion from the equation, you make better decisions. There’s no holding onto a position because you think it might change. There’s only analyzing the facts and deciding based on what is happening, not what might happen.

IBM’s open APIs and developer-friendly portals charge per API call once a product is live. This sort of scalability makes AI accessible to anyone, regardless of size or motivation. And, as you can see from the below chart, ETF providers who aren’t taking advantage of AI are losing out on revenue.

Since AI doesn’t need to sleep, it can be working 24/7, even when the markets are closed, trying strategies that might be difficult to execute for traders. And because of the amount of data available, risk is mitigated because AI will know when to get out before it’s too late. An AI system can make daily stock recommendations that the ETF manager can then use to shift positions, increasing alpha.

Compete or Go Home

An important aspect of any AI strategy is partnering with external developers. Because, in order to compete with the top financial firms in your sector, you need to leverage machine learning or risk being left behind. In fact, you might already be.